BUG: concat fails if indexes are all the same and keys are not unique (#43596)

Author: rhshadrach

doc/source/whatsnew/v1.4.0.rst

@@ -486,6 +486,7 @@ Reshaping
 - Bug in :meth:`DataFrame.append` failing to retain dtypes when appended columns do not match (:issue:`43392`)
 - Bug in :func:`concat` of ``bool`` and ``boolean`` dtypes resulting in ``object`` dtype instead of ``boolean`` dtype (:issue:`42800`)
 - Bug in :func:`crosstab` when inputs are are categorical Series, there are categories that are not present in one or both of the Series, and ``margins=True``. Previously the margin value for missing categories was ``NaN``. It is now correctly reported as 0 (:issue:`43505`)
+- Bug in :func:`concat` would fail when the ``objs`` argument all had the same index and the ``keys`` argument contained duplicates (:issue:`43595`)
 
 Sparse
 ^^^^^^

pandas/core/reshape/concat.py

@@ -695,7 +695,7 @@ def _make_concat_multiindex(indexes, keys, levels=None, names=None) -> MultiInde
         else:
             levels = [ensure_index(x) for x in levels]
 
-    if not all_indexes_same(indexes):
+    if not all_indexes_same(indexes) or not all(level.is_unique for level in levels):
         codes_list = []
 
         # things are potentially different sizes, so compute the exact codes

pandas/tests/reshape/concat/test_concat.py

@@ -3,11 +3,16 @@
     deque,
 )
 from decimal import Decimal
-from warnings import catch_warnings
+from warnings import (
+    catch_warnings,
+    simplefilter,
+)
 
 import numpy as np
 import pytest
 
+from pandas.errors import PerformanceWarning
+
 import pandas as pd
 from pandas import (
     DataFrame,
@@ -560,6 +565,22 @@ def test_duplicate_keys(keys):
     tm.assert_frame_equal(result, expected)
 
 
+def test_duplicate_keys_same_frame():
+    # GH 43595
+    keys = ["e", "e"]
+    df = DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]})
+    result = concat([df, df], axis=1, keys=keys)
+    expected_values = [[1, 4, 1, 4], [2, 5, 2, 5], [3, 6, 3, 6]]
+    expected_columns = MultiIndex.from_tuples(
+        [(keys[0], "a"), (keys[0], "b"), (keys[1], "a"), (keys[1], "b")]
+    )
+    expected = DataFrame(expected_values, columns=expected_columns)
+    with catch_warnings():
+        # result.columns not sorted, resulting in performance warning
+        simplefilter("ignore", PerformanceWarning)
+        tm.assert_frame_equal(result, expected)
+
+
 @pytest.mark.parametrize(
     "obj",
     [